EP4300111A1 - Système d'estimation de l'état de santé d'un bloc-batterie et procédé associé - Google Patents

Système d'estimation de l'état de santé d'un bloc-batterie et procédé associé Download PDF

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Publication number
EP4300111A1
EP4300111A1 EP23180316.4A EP23180316A EP4300111A1 EP 4300111 A1 EP4300111 A1 EP 4300111A1 EP 23180316 A EP23180316 A EP 23180316A EP 4300111 A1 EP4300111 A1 EP 4300111A1
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EP
European Patent Office
Prior art keywords
battery pack
state
health
parameters
processor
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
EP23180316.4A
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German (de)
English (en)
Inventor
Sundaraaman K.V.
Salahuddin Ahamad
Parmender Singh
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Exicom Tele Systems Ltd
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Exicom Tele Systems Ltd
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Filing date
Publication date
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Publication of EP4300111A1 publication Critical patent/EP4300111A1/fr
Pending legal-status Critical Current

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G01R31/392—Determining battery ageing or deterioration, e.g. state of health
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L58/00—Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles
    • B60L58/10—Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles for monitoring or controlling batteries
    • B60L58/16—Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles for monitoring or controlling batteries responding to battery ageing, e.g. to the number of charging cycles or the state of health [SoH]
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G01R31/382—Arrangements for monitoring battery or accumulator variables, e.g. SoC
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G01R31/385—Arrangements for measuring battery or accumulator variables
    • G01R31/387—Determining ampere-hour charge capacity or SoC
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G01R31/396—Acquisition or processing of data for testing or for monitoring individual cells or groups of cells within a battery
    • H—ELECTRICITY
    • H01—ELECTRIC ELEMENTS
    • H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
    • H01M10/00—Secondary cells; Manufacture thereof
    • H01M10/42—Methods or arrangements for servicing or maintenance of secondary cells or secondary half-cells
    • H01M10/425—Structural combination with electronic components, e.g. electronic circuits integrated to the outside of the casing
    • H—ELECTRICITY
    • H01—ELECTRIC ELEMENTS
    • H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
    • H01M10/00—Secondary cells; Manufacture thereof
    • H01M10/42—Methods or arrangements for servicing or maintenance of secondary cells or secondary half-cells
    • H01M10/48—Accumulators combined with arrangements for measuring, testing or indicating the condition of cells, e.g. the level or density of the electrolyte
    • H01M10/482—Accumulators combined with arrangements for measuring, testing or indicating the condition of cells, e.g. the level or density of the electrolyte for several batteries or cells simultaneously or sequentially
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G01R31/374—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC] with means for correcting the measurement for temperature or ageing
    • H—ELECTRICITY
    • H01—ELECTRIC ELEMENTS
    • H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
    • H01M10/00—Secondary cells; Manufacture thereof
    • H01M10/42—Methods or arrangements for servicing or maintenance of secondary cells or secondary half-cells
    • H01M10/425—Structural combination with electronic components, e.g. electronic circuits integrated to the outside of the casing
    • H01M2010/4278—Systems for data transfer from batteries, e.g. transfer of battery parameters to a controller, data transferred between battery controller and main controller
    • H—ELECTRICITY
    • H01—ELECTRIC ELEMENTS
    • H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
    • H01M2220/00—Batteries for particular applications
    • H01M2220/20—Batteries in motive systems, e.g. vehicle, ship, plane

Definitions

  • the present invention relates to a battery pack and more particularly relates to State of Health (SOH) of the battery pack.
  • SOH State of Health
  • Electric energy stored in devices such as batteries are, of late being used as energy sources in applications such as transportation, telecom and the like.
  • These batteries include multiple cells connected to one another in one of series and parallel, and combination thereof.
  • the batteries are subject to charging and discharging processes repeatedly.
  • the battery tends to undergo an irreversible capacity degradation due to various side reactions and physical changes that may occur during charging/discharging process, leading to performance deterioration and limiting cycle life of the battery.
  • SEI solid-electrolyte interphase
  • State of health is a parameter quantitatively representing change of battery capacity characteristics caused by an aging effect and indicates degree of battery capacity degradation. Therefore, if an accurate SOH is estimated, a battery can be replaced at a proper time and can be protected from over-charging and over-discharging by controlling battery capacity for charge and discharge based on the battery usage time.
  • One or more embodiments of the present invention provide a system and method for estimation of a State of Health (SOH) of a battery pack.
  • SOH State of Health
  • a method for estimation of State of Health (SOH) of a battery pack includes receiving, at a transceiver, a set of operational parameters pertaining to an operation of each of a plurality of cells of the battery pack. On receiving, the method includes determining, by the processor, a first state of health of the battery pack utilizing the set of operational parameters and a first set of stress parameters. Subsequently, the method includes receiving, at the transceiver, a discharge profile of one an exemplary battery pack and the battery pack to determine a discharge capacity of one of the exemplary battery pack and the battery pack utilizing the discharge profile.
  • SOH State of Health
  • the method includes determining, by the processor, a second state of health of the battery pack based on the determined discharge capacity. Thereafter, the method includes utilizing, by the processor, the first state of health and the second state of health to determine a second set of stress parameters of the battery pack for each of a plurality of State of Charge (SOC) ranges of the battery pack. Further, the method includes dynamically selecting, by the processor, at least of the second set of stress parameters from the second set of stress parameters, wherein the at least one of the second set of stress parameters corresponds to at least one SOC range of the plurality of SOC ranges.
  • SOC State of Charge
  • the method includes determining, by the processor, a third state of health of the battery pack based on the at least one selected second set of stress parameters and the set of operational parameters. Further, the method includes determining, by the processor, a deviation parameter based on the first and the third state of health of the battery pack. Furthermore, the method includes transmitting, by the processor, an ideal state of health signal to one of a server and a user device of an electric vehicle in response to the determined deviation parameter being greater than a pre-defined threshold.
  • a system for estimation a State of Health (SOH) of the battery pack includes a memory including executable instructions and a transceiver.
  • the transceiver receives a set of operational parameters pertaining to an operation of each of a plurality of cells of the battery pack and a discharge profile of one an exemplary battery pack and the battery pack to determine a discharge capacity of one of the exemplary battery pack and the battery pack utilizing the discharge profile.
  • the system further includes at least one processor in communication with the memory and the transceiver. The at least one processor is configured to determine a first state of health of the battery pack utilizing the set of operational parameters and a first set of stress parameters.
  • the at least one processor is further configured to determine a second state of health of the battery pack based on the determined discharge capacity. Thereafter, the at least one processor is configured to utilize the first state of health and the second state of health to determine a second set of stress parameters of the battery pack for each of a plurality of State of Charge (SOC) ranges of the battery pack. On determination, the at least one processor is configured to dynamically select at least of the second set of stress parameters from the second set of stress parameters, wherein the at least one of the second set of stress parameters corresponds to at least one SOC range of the plurality of SOC ranges. On selection, the at least one processor is configured to determine a third state of health of the battery pack based on the at least one selected second set of stress parameters and the set of operational parameters.
  • SOC State of Charge
  • the at least one processor is configured to determine a deviation parameter based on the first and the third state of health of the battery pack and transmit an ideal state of health signal to one of a server and a user device of an electric vehicle in response to the determined deviation parameter being greater than a pre-defined threshold.
  • battery pack in yet another embodiment, battery pack is disclosed.
  • the batter pack includes a plurality of cells arranged within the battery pack, a sensory unit electrically coupled to the plurality of cells to measure a set of operational parameters pertaining to an operation of each of a plurality of cells of the battery pack, and a battery telematics unit communicably coupled to the plurality of cells.
  • the battery pack further includes at least one processor communicably coupled to each of the sensory unit and the battery telematics unit. The at least one processor is configured to receive the set of operational parameters pertaining to an operation of each of a plurality of cells of the battery pack.
  • the at least one processor is configured to receive a discharge profile of one an exemplary battery pack and the battery pack to determine a discharge capacity of one of the exemplary battery pack and the battery pack utilizing the discharge profile.
  • the at least one processor is configured to determine a first state of health of the battery pack utilizing the set of operational parameters and a first set of stress parameters.
  • the at least one processor is further configured to determine a second state of health of the battery pack based on the determined discharge capacity. Thereafter, the at least one processor is configured to utilize the first state of health and the second state of health to determine a second set of stress parameters of the battery pack for each of a plurality of State of Charge (SOC) ranges of the battery pack.
  • SOC State of Charge
  • the at least one processor is configured to dynamically select at least of the second set of stress parameters from the second set of stress parameters, wherein the at least one of the second set of stress parameters corresponds to at least one SOC range of the plurality of SOC ranges.
  • the at least one processor is configured to determine a third state of health of the battery pack based on the at least one selected second set of stress parameters and the set of operational parameters. Thereafter, the at least one processor is configured to determine a deviation parameter based on the first and the third state of health of the battery pack and transmit an ideal state of health signal to one of a server and a user device of an electric vehicle in response to the determined deviation parameter being greater than a pre-defined threshold.
  • FIG. 1 illustrates a block diagram of an environment 100 to which a system 105 for estimation of a State of Health (SOH) of a battery pack 110 is implemented, according to one or more embodiments of the present invention.
  • the battery pack 110 is employed as an energy source in applications such as transportation, telecom, household appliances, and the like.
  • the battery pack 110 may be utilized as an energy source for an electric vehicle.
  • the illustrated embodiment depicts a single battery pack 110, it is to be understood that multiple battery packs may be used as per the requirement, without deviating from the scope of the present disclosure.
  • the battery pack 110 includes a plurality of cells 115 arranged therein. Each of the plurality of cells 115 is electrically coupled to the each other in one of a series connection, a parallel connection and a combination thereof.
  • each of the plurality of cells 115 is one of, but not limited to, a Lithium ion (Li-ion), a Lead acid gel, and Nickel metal hydride.
  • composition of each of the plurality of cells 115 is lithium or lithium polymer cells (referred to as "lithium") combined with a nickel hydrate battery cells.
  • any suitable battery cell composition may be used, including, but not necessarily limited to, lithium ion, zinc air, zinc oxide, super charged zinc oxide, and fuel cells.
  • the battery pack 115 further includes a plurality of sensors 120 communicably coupled to at least each of the plurality of cells 115 of the battery pack 110.
  • the plurality of sensors 120 is configured to measure a set of operational parameters pertaining to each of the plurality of cells 115 of the battery pack 110.
  • the set of operational parameters includes data corresponding to at least one of, but not limited to, depth of discharge, rate of charging/discharging, mean of state of charge (SOC), upper and lower and cut off SOC, and a combination thereof of the battery pack 110.
  • the battery pack 110 further includes a battery telematics unit 125 communicably coupled to the plurality of sensors 120 and the system 105 of the battery pack 110.
  • the battery telematics unit 125 is configured to receive and temporarily store the set of operational parameters of each of the plurality of cells 115 of the battery pack 110.
  • the battery telematics unit 125 is further configured to transfer the set of operational parameters of each of the plurality of cells 115 to the system 105 to aid in estimation of the SOH of the battery pack 110.
  • the system 105 as per the illustrated embodiment in FIG. 1 is embodied as an integral part of the battery pack 110. In alternate embodiments, the system 105 is located at a remote location communicably coupled to the battery telematics unit 125 of the battery pack 110.
  • the system 105 is further configured to transmit the set of operational parameters to a server 130 via a network 135.
  • copy of the data pertaining to the set of operational parameters is automatically deleted from the system 105.
  • the system 105 is not burdened with large volume of data beyond the capacity of the system 105, thereby ensuring that effective monitoring service is provided and improving the operational efficiency of the system 105.
  • the server 130 may be implemented in a variety of computing systems, such as a mainframe computer, a network server, cloud, and the like.
  • the server 130 is in communication with the system 105 of the battery pack 110 via the network 135.
  • a Secure Hardware Extension (SHE) unit is embedded within the battery pack 110.
  • the SHE unit ensures that a secure communication of data takes place between the system 105 and the server 130, thereby preventing third party access to data.
  • the network 135 can include wired and/or wireless connections such as, but not limited to, local area network (LAN), Bluetooth, Near Field Communication (NFC), infrared, WIFI, GPRS, LTE, Edge and the like.
  • the system 105 is in communication with a user device 140 via the network 135.
  • the user device 140 receives notifications pertaining to the SOH of the battery pack 110.
  • the user device 140 is communicably coupled to the server 135.
  • one of the server 130 and the system 105 is configured to provide the user with periodic reports regarding SOH of the battery pack 110.
  • the user device 140 is one of, but not limited to, a mobile phone, a portable computer, a personal digital assistant, a handheld device, a laptop computer, and a communication device, such as, but not limited to, a display unit of the electric vehicle.
  • FIG. 2 illustrates a schematic representation of the system 105 for the estimation of the SOH of the battery pack 110, according to one or more embodiments of the present invention.
  • the system 105 is communicably coupled to the battery telematics unit 125 and the plurality of cells 115 of the battery pack 110.
  • the system 105 is configured to receive data pertaining to the set of operational parameters of each of the plurality of cells of the battery pack 110 for the estimation of the SOH of the battery pack 110.
  • the system 105 includes a include a transceiver 205, at least one processor 210, an input/output (I/O) interface unit 215, a memory 220, and a plurality of functionality modules 225.
  • a transceiver 205 includes a transceiver 205, at least one processor 210, an input/output (I/O) interface unit 215, a memory 220, and a plurality of functionality modules 225.
  • the transceiver 205 of the system 105 may be implemented as a device adapted to aid in one of receiving and transmitting at least one of, but not limited to, the set of operational parameters and the estimated SOH to the at least one processor 210, the server 130, and the user device 140.
  • the transceiver 205 is configured to receive the set of operational parameters pertaining to operation of each of the plurality of cells 115 of the battery pack 110.
  • the transceiver 205 is further communicably coupled to the at least one processor 210.
  • the at least one processor 210 may be implemented as one or more microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, state machines, logic circuitries, and/or any devices that manipulate signals based on operational instructions. Among other capabilities, the at least one processor 210 is configured to fetch and execute computer-readable instructions stored in the memory 220.
  • the I/O interface unit 215 may include a variety of software and hardware interfaces, for example, a web interface, a graphical user interface, Light Emitting Diode (LED) and the like.
  • the I/O interface unit 215 may allow the user to interact with the system 105 directly or through the user device 140. Further, the I/O interface unit 215 may enable the system 105 to communicate with other computing devices, such as the server 130 and external data servers (not shown).
  • the I/O interface 215 may facilitate multiple communications within a wide variety of networks and protocol types, including wired networks, for example, LAN, cable, etc., and wireless networks, such as WLAN, cellular, or satellite.
  • the I/O interface unit 215 may include one or more ports for connecting a number of devices to one another or to another server.
  • the memory 220 may include any computer-readable medium known in the art including, for example, volatile memory, such as static random access memory (SRAM) and dynamic random access memory (DRAM), and/or non-volatile memory, such as read only memory (ROM), erasable programmable ROM, flash memories, hard disks, optical disks, and magnetic tapes.
  • volatile memory such as static random access memory (SRAM) and dynamic random access memory (DRAM)
  • DRAM dynamic random access memory
  • non-volatile memory such as read only memory (ROM), erasable programmable ROM, flash memories, hard disks, optical disks, and magnetic tapes.
  • FIG. 3 illustrates an interaction of the at least one processor 210 with the plurality of functionality modules 225 to estimate the SOH of the battery pack 110, according to one or more embodiments of the present invention.
  • module refers to logic embodied in hardware or firmware, or to a collection of software instructions, written in a programming language, such as, Java, C, C++, and the like.
  • One or more software instructions in the said modules may be embedded in firmware, such as an EPROM.
  • the said modules may include connected logic units, such as gates and flip-flops, and may further include programmable units, such as programmable gate arrays or processors.
  • the said modules as described herein may be implemented as either software and/or hardware modules and may be stored in any type of computer-readable medium or other computer storage device.
  • any function or operation that has been described as being performed by a module could alternatively be performed by a different server, by the cloud computing platform, or a combination thereof.
  • the at least one processor 210 is configured to interact with the plurality of functionality modules 225 for the estimation of the SOH of the battery pack 110.
  • the plurality of functionality modules 225 is in communication with the processor 210 and the processor 210 controls the operation of the plurality of functionality modules 235 for the estimation of the SOH of the battery pack 110.
  • each of the plurality of functionality modules 225 explained below may be configured to independently perform the respective functions.
  • the plurality of functionality modules 225 is an integral component of the processor 210.
  • the plurality of functionality modules 225 includes, but not limited to, a SOH estimation module 305, a discharge profile module 310, a parameter estimation module 315, a deviation determination module 320, a decision module 325, and repository module 330.
  • the battery pack 110 includes the plurality of sensors 120 to measure the set of operational parameters pertaining to the operation of each of the plurality of cells 115 of the battery pack 110.
  • the battery telematics unit 125 receives the same, and thereafter transmits the set of operational parameters to the transceiver 205 of the system 105. Subsequently, the transceiver 205 transmits the set of operational parameters to the SOH estimation module 305.
  • the SOH estimation module 305 is configured to estimate a first SOH of the battery pack 110.
  • the SOH estimation module 305 utilizes a first set of stress parameters (ki) for determining the first SOH.
  • the first set of stress parameters (k i ) includes multiple parameters that adversely affects operation of the battery pack 110 with respect to parameters such as, but not limited to, the charging rate, State of Charge (SOC) mean, and Depth of Discharge (DOD) of the battery pack 110 considering a current condition in which the battery pack 110 is operating and associated current temperature at which the battery pack 110 is operating.
  • the current condition of the battery pack 110 may correspond to a mechanical degradation, such as but not limited to, Solid Electrolyte Interphase (SEI) growth on each of the plurality of cells 115 of the battery pack 110.
  • SEI growth may vary based on a number of cycles.
  • the first set of stress parameters (k i ) includes a set of six (6) parameters (k 1 , k 2 , k 3 , k 4 , k 5 , k 6 ).
  • the first set of stress parameters (ki) may include more than 6 parameters without deviating from the scope of the present disclosure.
  • the SOH estimation module 305 utilizes a global minima initialization to assign a predefined value to each of the first set of stress parameters (k 1 , k 2 , k 3 , k 4 , k 5 , k 6 ) for determining the first SOH.
  • the predefined value for each of the first set of stress parameters (k 1 , k 2 , k 3 , k 4 , k 5 , k 6 ) is set at a minimum value.
  • the SOH estimation module 305 utilizes the set of operational parameters, such as the depth of discharge of the battery pack, rate of charging/discharging, mean of state of charge (SOC), and upper and lower and cut off SOC of the battery pack 110 (otherwise termed as the SOC% range), and the first set of stress parameters to determine the first SOH of the battery pack 110 for a known number of cycles (n).
  • set of operational parameters such as the depth of discharge of the battery pack, rate of charging/discharging, mean of state of charge (SOC), and upper and lower and cut off SOC of the battery pack 110 (otherwise termed as the SOC% range)
  • the SOH estimation module 305 advantageously, optimizes the predefined value to each of the first set of stress parameters (k 1 , k 2 , k 3 , k 4 , k 5 , k 6 ) so that a predefined error between the first SOH (or otherwise termed as the experimental SOH) and a SOH value that may be determined based on simulations, is met.
  • the SOH estimation module 305 receives a discharge profile of one of an exemplary battery pack and the battery pack 110 in use from the discharge profile module 310.
  • the discharge profile includes a maximal releasable capacity (C max ) of one of the experimental battery pack and the battery pack after 'n' number of cycles.
  • the SOH of the experimental battery pack is a percentage of the maximal releasable capacity (C max ) relative to a rated capacity (C rated ) of one of the experimental battery pack and the battery pack 110.
  • the discharge profile includes a set of experimental parameters pertaining to the depth of discharge of the exemplary battery pack, rate of charging/discharging, mean of state of charge (SOC), and upper and lower cut off SOC (otherwise termed as the SOC% range) of the exemplary battery pack.
  • the discharge profile includes a set of experimental parameters pertaining to the depth of discharge of the battery pack 100, rate of charging/discharging, mean of state of charge (SOC), and upper and lower cut off SOC of the battery pack 110 (otherwise termed as the SOC% range).
  • the set of experimental parameters is based on experiments conducted on one of the experimental battery pack and the battery pack 110 for multiple SOC% ranges, such as, but not limited to, 0-100, 5-100, 10-100, 0-95, 5-95, 10-95, 0-90, 5-90, and 10-90.
  • the discharge profile module 310 is configured to receive the discharge profile of the exemplary battery pack from the server 130 via the network 135.
  • the discharge profile of one of the exemplary battery and the battery pack is stored in a repository module 330.
  • the SOH estimation module 305 receives a discharge profile of one of an exemplary battery pack and the battery pack 110 from the discharge profile module 310. On receiving, the SOH estimation module 305 estimates a second SOH of one of the exemplary battery pack and the battery pack 110 utilizing the set of experimental parameters of the discharge profile, or otherwise based on the determined discharge capacity of one of an exemplary battery pack and the battery pack 110. Further, in one embodiment, the temperature is considered to be a constant.
  • n is the number of cycles
  • DOD is the depth of discharge
  • SOC M is the mean state of charge
  • a and b are parameters and assumed to be the function of the DOD
  • C-rate is the function of the DOD
  • SOC M is the function of the cycle number at a given temperature.
  • the second SOH is determined utilizing the Eq. 2 and based upon physical and chemical events occurring inside the battery pack 110 during one of charging and discharging process of the same.
  • the function f 1 in the Eq. 2 corresponds to a SEI layer growth associated with a failure mechanism of each of the plurality of cells 115 of the battery pack 110 and the function f 2 corresponds to a cycling aging due to mechanical stress generated in the electrode material of each of the plurality of cells 115 of the battery pack 110 during cycling process.
  • the SOH estimation module 305 in communication with the parameter estimation module 315 utilizes the Eq. 1 and the Eq. 2 as provided above to determine a second set of stress parameters (k i ) utilizing models such as, but not limited to, Levenberg- Marquardt model.
  • the parameter estimation module 315 determines multiple sets of stress parameters (k i ). Each of the multiple second set of stress parameters corresponds to each of the multiple SOC% ranges, such as, but not limited to, 0-100, 5-100, 10-100, 0-95, 5-95, 10-95, 0-90, 5-90, and 10-90, respectively. Accordingly, the parameter estimation module determines the second set of stress parameter for each of the multiple SOC % ranges.
  • the second set of stress parameters (ki) includes six (6) parameters (k 1 , k 2 , k 3 , k 4 , k 5 , k 6 ).
  • the second set of stress parameters (ki) may include more than 6 parameters without deviating from the scope of the present disclosure.
  • the parameter estimation module 315 transfers the determined second set of stress parameters (k 1 , k 2 , k 3 , k 4 , k 5 , k 6 ) to the SOH estimation module 305. Thereafter, the SOH estimation module 305 dynamically selects at least one of the second set of stress parameters from the multiple sets of stress parameters.
  • the SOH estimation module 305 utilizes the dynamically selected second set of stress parameters and set of operational parameters as per the Eq. 1 as provided above to determine a third SOH of the battery pack 110.
  • the SOH estimation module 305 provides the first SOH and the third SOH as determined to the deviation determination module 320.
  • the deviation determination module 320 is configured to determine a deviation parameter (R 2 ) based on the first and the third SOH of the battery pack 110.
  • the deviation parameter module 320 utilizes each of the first and the third SOH to determine an experimental capacity ( C E ) and a theoretical capacity ( C T ) of the battery pack 110.
  • the deviation determination module 320 is configured to compare the deviation parameter (R 2 ) to a pre-defined threshold.
  • the pre-defined threshold is set at 0.9. In an alternate embodiment, the pre-defined threshold is about 0.9.
  • the deviation determination module 320 instructs the SOH estimation module 305 to determine the third SOH of the battery pack utilizing the set of operational parameters and at least one of remaining second set of stress parameters from the multiple second set of stress parameters not dynamically selected previously.
  • the deviation determination module 320 instructs the decision module 325 of the same. Consequently, the decision module 325 is configured to transmit an ideal SOH signal to one of the server 130, the user device 140, and a combination thereof.
  • FIG. 4 is a flow chart of a method 400 for estimation of State of Health (SOH) of a battery pack 110 utilizing a system 105, according to one or more embodiments of the present invention.
  • SOH State of Health
  • the method 400 is described with the embodiments as illustrated in FIGs 2-3 . Further, in order to avoid repetition and for the sake of brevity, the description for the FIGs 2-3 should be referred and should nowhere be construed as limiting the scope of the present disclosure.
  • the method 400 includes the step of receiving, at a transceiver 205, a set of operational parameters pertaining to an operation of each of a plurality of cells 115 of the battery pack 110.
  • the method 400 includes the step of determining, by the processor 210, a first state of health of the battery pack 110 utilizing the set of operational parameters and a first set of stress parameters.
  • the method 400 includes the step of receiving, at the transceiver 205, a discharge profile of one an exemplary battery pack and the battery pack 110 to determine a discharge capacity of one of the exemplary battery pack and the battery pack 110 utilizing the discharge profile.
  • the method 400 includes the step of determining, by the processor 210, a second state of health of the battery pack 110 based on the determined discharge capacity.
  • the method 400 includes the step of utilizing, by the processor 210, the first state of health and the second state of health to determine a second set of stress parameters of the battery pack 110 for each of a plurality of State of Charge (SOC) ranges of the battery pack 110.
  • SOC State of Charge
  • the method 400 includes the step of dynamically selecting, by the processor 210, at least one of the second set of stress parameter from the second set of stress parameters.
  • the at least one of the second set of stress parameter corresponds to at least one SOC range of the plurality of SOC ranges.
  • the method 400 includes the step of determining, by the processor 210, a third state of health of the battery pack 110 based on the at least one selected second set of stress parameters and the set of operational parameters.
  • the method 400 includes the step of determining, by the processor 210, a deviation parameter based on the first and the third state of health of the battery pack 110.
  • the method 400 includes the step of transmitting, by the processor, an ideal state of health signal to one of a server 130 and a user device 140 of an electric vehicle in response to the determined deviation parameter being greater than a pre-defined threshold.

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  • Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Physics & Mathematics (AREA)
  • Manufacturing & Machinery (AREA)
  • General Chemical & Material Sciences (AREA)
  • Electrochemistry (AREA)
  • Chemical Kinetics & Catalysis (AREA)
  • Chemical & Material Sciences (AREA)
  • Sustainable Development (AREA)
  • Microelectronics & Electronic Packaging (AREA)
  • Mechanical Engineering (AREA)
  • Transportation (AREA)
  • Power Engineering (AREA)
  • Sustainable Energy (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Charge And Discharge Circuits For Batteries Or The Like (AREA)
  • Secondary Cells (AREA)
EP23180316.4A 2022-06-28 2023-06-20 Système d'estimation de l'état de santé d'un bloc-batterie et procédé associé Pending EP4300111A1 (fr)

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Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20200227791A1 (en) * 2017-09-14 2020-07-16 Abb Schweiz Ag Method and System For Controlling a Rechargeable Battery
US20210268927A1 (en) * 2020-02-28 2021-09-02 Denso Corporation Information calculation system
US20220149645A1 (en) * 2020-11-10 2022-05-12 Tata Consultancy Services Limited Method and system for optimizing operation of battery pack of an electric vehicle

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20200227791A1 (en) * 2017-09-14 2020-07-16 Abb Schweiz Ag Method and System For Controlling a Rechargeable Battery
US20210268927A1 (en) * 2020-02-28 2021-09-02 Denso Corporation Information calculation system
US20220149645A1 (en) * 2020-11-10 2022-05-12 Tata Consultancy Services Limited Method and system for optimizing operation of battery pack of an electric vehicle

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